ollama - 💡(How to fix) Fix Still crashing on Ollama 0.17.1 with Intel Arc 140V (iGPU, Vulkan) [2 comments, 2 participants]

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ollama/ollama#14610Fetched 2026-04-08 00:33:38
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Error Message

Exception 0xc0000005 in ggml_backend_sched_graph_compute_async rax=0x0 (null pointer dereference)

Code Example

Exception 0xc0000005 in ggml_backend_sched_graph_compute_async
rax=0x0 (null pointer dereference)

---
RAW_BUFFERClick to expand / collapse

What is the issue?

Still crashing on Ollama 0.17.1 with Intel Arc 140V (iGPU, Vulkan)

Tried GGML_VK_DISABLE_COOPMAT=1, GGML_VK_DISABLE_COOPMAT2=1, and GGML_VK_NO_PIPELINE_CACHE=1 — coopmat is now disabled (matrix cores: none) but the crash persists at the same location:

Exception 0xc0000005 in ggml_backend_sched_graph_compute_async
rax=0x0 (null pointer dereference)

The model loads fully (25/25 layers offloaded to Vulkan), then crashes on the first inference batch. This is reproducible every time on qwen3.5 — other models work fine on the same GPU/setup.

Relevant log output

OS

Docker, Windows

GPU

Intel

CPU

Intel

Ollama version

0.17.1

extent analysis

Fix Plan

To resolve the null pointer dereference issue in ggml_backend_sched_graph_compute_async, we need to ensure that all pointers are properly initialized before use.

  • Update the ggml library to the latest version to ensure any known issues are fixed.
  • Verify that the Vulkan pipeline is correctly set up and that the coopmat disable flags are properly applied.
  • Modify the code to check for null pointers before calling ggml_backend_sched_graph_compute_async.

Example code snippet to check for null pointers:

if (graph != NULL && sched != NULL) {
    ggml_backend_sched_graph_compute_async(graph, sched);
} else {
    // Handle the error, e.g., log and exit
    printf("Error: Null pointer encountered\n");
    exit(1);
}

Verification

To verify the fix, run the application with the updated code and check for the null pointer dereference error. If the error persists, further debugging may be required to identify the root cause.

Extra Tips

  • Ensure that the Vulkan SDK and drivers are up-to-date.
  • Consider adding additional error checking and logging to help diagnose any future issues.
  • If using Docker, verify that the container has the necessary dependencies and permissions to access the GPU.

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